FDA-approved drugs containing dimethylamine pharmacophore: a review of the last 50 years.

Dimethylamine (DMA) derivatives represent a promising class of compounds with significant potential in the field of medicinal chemistry. DMA derivatives exhibit a diverse range of pharmacological activities, including antimicrobial, antihistaminic, anticancer, and analgesic properties. Their unique chemical structure allows for the modulation of various biological targets, making them valuable candidates for the treatment of numerous diseases. Synthetic strategies for the preparation of DMA derivatives vary depending on the desired biological activity and target molecule. Common synthetic routes involve the modification of the DMA scaffold through functional group manipulation, scaffold hopping, or combinatorial chemistry approaches. Therapeutically, DMA derivatives have shown promise in the treatment of infectious diseases, especially bacterial infections. Additionally, by focusing on particular biochemical pathways involved in tumor growth and metastasis, DMA-based drugs have shown anticancer activity. In addition to their direct pharmacological effects, DMA derivatives can serve as valuable tools in drug delivery systems, prodrug design, and molecular imaging techniques, enhancing their utility in medicinal chemistry research. Overall, DMA derivatives represent a versatile class of compounds with immense potential in medicinal chemistry. Further research and development efforts are warranted to explore their full therapeutic capabilities and optimize their clinical utility in the treatment of various diseases. This article outlines the pharmacological properties, synthetic strategies, and therapeutic applications of DMA derivatives of FDA approved drugs, highlighting their importance in drug discovery and development.

In Silico Molecular Docking and Molecular Dynamics Analysis of Antimicrobial Triazole Derivatives: Insights from Synthesis, Computational and In Vitro Studies.

INTRODUCTION: In the ongoing fight against bacterial resistance to antibiotics, this study focuses on synthesizing and evaluating 1,2,4-triazole derivatives to explore their potential as new antibacterial agents. 1,2,4-Triazole compounds are promising drug candidates with a wide range of therapeutic effects, including pain relief, antiseptic, antimicrobial, antioxidant, antiurease, anti-inflammatory, diuretic, anticancer, anticonvulsant, antidiabetic, and antimigraine properties. METHOD: The structures of all the synthesized compounds were identified using their physicochemical properties and spectral techniques, such as IR and NMR. These compounds were then evaluated in molecular docking studies against antimicrobial activity in vitro and further supported by molecular dynamics studies. RESULT: Compound 7, featuring a 6-chloro group on the phenyl ring, emerged as the most effective against Gram-positive S. aureus compared to the standard antibiotic ciprofloxacin. Docking studies revealed high and comparable affinities for all ten ligands, with compounds 4 and 6 showing the best-docked activity against Penicillin Acylase mutants. Further, compounds 6 and 10 displayed significant affinity against D-alanine-D-alanine ligase (DDL) from Yersinia pestis during 100 ns MD simulation. CONCLUSION: Notably, compound 7 demonstrated the highest binding score to the 5C1P protein, suggesting its potential as a lead molecule for the development of potent and safer antimicrobial agents. This research contributes valuable insights into addressing the escalating challenge of bacterial resistance.

3D-QSAR, Pharmacophore Modeling, ADMET, and DFT Studies of Halogenated Conjugated Dienones as Potent MAO-B Inhibitors.

INTRODUCTION: It has been reported that the extension of conjugation in chalcone scaffolds considerably enhanced the potency, selectivity, reversibility, and competitive mode of MAO-B inhibition. In this study, using the experimental results of IC50 values of fifteen halogenated conjugated dienone derivatives (MK1-MK15) against MAO-B, we developed a 3DQSAR model. METHODS: Further, we created a 3D pharmacophore model in active compounds in the series. The built model selected three variables (G2U, RDF115m, RDF155m) among the 653 AlvaDesc molecular descriptors, with a r2 value of 0.87 and a Q2 cv for cross-validation equal to 0.82. The three variables were mostly associated with the direction of symmetry and the likelihood of discovering massive atoms at great distances. The evaluated molecules exhibited a good correlation between experimental and predicted data, indicating that the IC50 value of the structure MK2 was related to the interatomic distances of 15.5 Å between bromine and chloro substituents. Furthermore, the molecules in the series with the highest activity were those with enhanced second component symmetry directional index from the 3D representation, which included the structures MK5 and MK6. RESULT: Additionally, a pharmacophore hypothesis was developed and validated using the decoy Schrodinger dataset, with an ROC score of 0.87 and an HHRR 1 fitness score that ranged from 2.783 to 3.00. The MK series exhibited a significant blood-brain barrier (BBB) permeability, according to exploratory analyses and in silico projections, and almost all analogues were expected to have strong BBB permeability. CONCLUSION: Further DFT research revealed that electrostatics were important in the interactions with MAO-B.

Inhibition of monoamine oxidases and neuroprotective effects: chalcones vs. chromones.

Eighteen compounds derived from two sub-series, (HC1-HC9) and (HF1-HF9), were synthesized and evaluated for their inhibitory activities against monoamine oxidase (MAO). HC (chalcone) series showed higher inhibitory activity against MAO-B than against MAO-A, whereas the HF (chromone) series showed reversed inhibitory activity. Compound HC4 most potently inhibited MAO-B with an IC50 value of 0.040 µM, followed by HC3 (IC50 = 0.049 µM), while compound HF4 most potently inhibited MAO-A (IC50 = 0.046 µM), followed by HF2 (IC50 = 0.075 µM). The selectivity index (SI) values of HC4 and HF4 were 50.40 and 0.59, respectively. Structurally, HC4 (4-OC2H5 in B-ring) showed higher MAO-B inhibition than other derivatives, suggesting that the -OC2H5 substitution of the 4-position in the B-ring contributes to the increase of MAO-B inhibition, especially -OC2H5 (HC4) > -OCH3 (HC3) > -F (HC7) > -CH3 (HC2) > -Br (HC8) > -H (HC1) in order. In MAO-A inhibition, the substituent 4-OC2H5 in the B-ring of HF4 contributed to an increase in inhibitory activity, followed by -CH3 (HF2), -F (HF7), -Br (HF8), -OCH3 (HF3), and-H (HF1). In the enzyme kinetics and reversibility study, the Ki value of HC4 for MAO-B was 0.035 ± 0.005 µM, and that of HF4 for MAO-A was 0.035 ± 0.005 µM, and both were reversible competitive inhibitors. We confirmed that HC4 and HF4 significantly ameliorated rotenone-induced neurotoxicity, as evidenced by the reactive oxygen species and superoxide dismutase assays. This study also supports the significant effect of HC4 and HF4 on mitochondrial membrane potential in rotenone-induced toxicity. A lead molecule was used for molecular docking and dynamic simulation studies. These results show that HC4 is a potent selective MAO-B inhibitor and HF4 is a potent MAO-A inhibitor, suggesting that both compounds can be used as treatment agents for neurological disorders.

Multireceptor Analysis for Evaluating the Antidiabetic Efficacy of Karanjin: A Computational Approach.

BACKGROUND: Diabetes mellitus, notably type 2, is a rising global health challenge, prompting the need for effective management strategies. Common medications such as metformin, insulin, repaglinide and sitagliptin can induce side effects like gastrointestinal disturbances, hypoglycemia, weight gain and specific organ risks. Plant-derived therapies like Karanjin from Pongamia pinnata present promising alternatives due to their historical use, holistic health benefits and potentially fewer adverse effects. This study employs in silico analysis to explore Karanjin's interactions with diabetes-associated receptors, aiming to unveil its therapeutic potential while addressing the limitations and side effects associated with conventional medications. METHODOLOGY: The research encompassed the selection of proteins from the Protein Data Bank (PDB), followed by structural refinement processes and optimization. Ligands such as Karanjin and standard drugs were retrieved from PubChem, followed by a comprehensive analysis of their ADMET profiling and pharmacokinetic properties. Protein-ligand interactions were evaluated through molecular docking using AutoDockTools 1.5.7, followed by the analysis of structural stability using coarse-grained simulations with CABS Flex 2.0. Molecular dynamics simulations were performed using Desmond 7.2 and the OPLS4 force field to explore how Karanjin interacts with proteins over 100 nanoseconds, focusing on the dynamics and structural stability. RESULTS: Karanjin, a phytochemical from Pongamia pinnata, shows superior drug candidate potential compared to common medications, offering advantages in efficacy and reduced side effects. It adheres to drug-likeness criteria and exhibits optimal ADMET properties, including moderate solubility, high gastrointestinal absorption and blood-brain barrier penetration. Molecular docking revealed Karanjin's highest binding energy against receptor 3L2M (Pig pancreatic alpha-amylase) at -9.1 kcal/mol, indicating strong efficacy potential. Molecular dynamics simulations confirmed stable ligand-protein complexes with minor fluctuations in RMSD and RMSF, suggesting robust interactions with receptors 3L2M. CONCLUSION: Karanjin demonstrates potential in pharmaceutical expansion for treating metabolic disorders such as diabetes, as supported by computational analysis. Prospects for Karanjin in pharmaceutical development include structural modifications for enhanced efficacy and safety. Nanoencapsulation may improve bioavailability and targeted delivery to pancreatic cells, while combination therapies could optimize treatment outcomes in diabetes management. Clinical trials and experimental studies are crucial to validate its potential as a novel therapeutic agent.

Design, synthesis, and in vitro and in silico studies of morpholine derived thiazoles as bovine carbonic anhydrase-II inhibitors.

Carbonic anhydrase CA-II enzyme is essential for maintaining homeostasis in several processes, including respiration, lipogenesis, gluconeogenesis, calcification, bone resorption, and electrolyte balance due to its vital function within cellular processes. Herein, we screened 25 newly synthesized thiazole derivatives and assessed their inhibitory potential against the zinc-containing carbonic anhydrase CA-II enzyme. Intriguingly, derivatives of thiazole exhibited varying degrees of inhibitory action against CA-II. The distinctive attribute of these compounds is that they can attach to the CA-II binding site and block its action. Morpholine based thiazoles can be strategically modified to improve bovine CA-II inhibitor binding affinity, selectivity, and pharmacokinetics. Thiazole and morpholine moieties can boost inhibitory efficacy and selectivity over other calcium-binding proteins by interacting with target bovine CA-II binding sites. The derivatives 23-26 exhibited greater affinity when compared to the standard acetazolamide. Furthermore, kinetic study of the most potent compound 24 was performed, which exhibited concentration dependent inhibition with a K i value of 9.64 ± 0.007 µM. Molecular docking, MD simulation and QSAR analysis was also carried out to elucidate the interactions, orientation, and conformational changes of these compounds within the active site of the enzyme. Moreover, pharmacokinetic assessments showed that most of the compounds possess attributes conducive to potential drug development.

Elucidating molecular mechanism and chemical space of chalcones through biological networks and machine learning approaches.

We developed a bio-cheminformatics method, exploring disease inhibition mechanisms using machine learning-enhanced quantitative structure-activity relationship (ML-QSAR) models and knowledge-driven neural networks. ML-QSAR models were developed using molecular fingerprint descriptors and the Random Forest algorithm to explore the chemical spaces of Chalcones inhibitors against diverse disease properties, including antifungal, anti-inflammatory, anticancer, antimicrobial, and antiviral effects. We generated and validated robust machine learning-based bioactivity prediction models (https://github.com/RatulChemoinformatics/QSAR) for the top genes. These models underwent ROC and applicability domain analysis, followed by molecular docking studies to elucidate the molecular mechanisms of the molecules. Through comprehensive neural network analysis, crucial genes such as AKT1, HSP90AA1, SRC, and STAT3 were identified. The PubChem fingerprint-based model revealed key descriptors: PubchemFP521 for AKT1, PubchemFP180 for SRC, PubchemFP633 for HSP90AA1, and PubchemFP145 and PubchemFP338 for STAT3, consistently contributing to bioactivity across targets. Notably, chalcone derivatives demonstrated significant bioactivity against target genes, with compound RA1 displaying a predictive pIC50 value of 5.76 against HSP90AA1 and strong binding affinities across other targets. Compounds RA5 to RA7 also exhibited high binding affinity scores comparable to or exceeding existing drugs. These findings emphasize the importance of knowledge-based neural network-based research for developing effective drugs against diverse disease properties. These interactions warrant further in vitro and in vivo investigations to elucidate their potential in rational drug design. The presented models provide valuable insights for inhibitor design and hold promise for drug development. Future research will prioritize investigating these molecules for mycobacterium tuberculosis, enhancing the comprehension of effectiveness in addressing infectious diseases.

Attenuation of adjuvant-induced arthritis with carnosic acid by inhibiting mPGES-1, COX-2, and bone loss in male SD rats.

OBJECTIVE: Rheumatoid arthritis (RA), a chronic inflammatory disease, is characterized by joint swelling, cartilage erosion, and bone destruction. This study investigated the therapeutic efficacy of Carnosic acid (CA), a natural compound with anti-inflammatory and antioxidant properties, in an adjuvant-induced arthritis model. METHODS: Paw swelling and arthritis index were measured. Oxidative stress markers, including lipid peroxidation and antioxidant enzyme levels, were assessed. Synovial tissue was analyzed for pro-inflammatory markers using real-time Q-PCR and Western blotting. The expression of mPGES-1 was determined by Western blotting. Peripheral neuropathic pain was assessed using cold and mechanical allodynia tests. Bone loss was quantitatively assessed through microcomputed tomography (µCT) scanning of femurs and X-ray radiography. Indomethacin-induced gastric ulcers were evaluated. Molecular docking studies were conducted to analyze the binding affinity of CA to mPGES-1. RESULTS: The CA treatment not only demonstrated a significant reduction in joint inflammation and paw swelling but also mitigated oxidative stress and improved the antioxidant defence system. CA inhibited microsomal prostaglandin E synthase-1 (mPGES-1) expression and the expression of pro-inflammatory molecules such as inducible nitric oxide synthase (iNOS) and cyclooxygenases-2 (COX-2), thus attenuating the arthritis symptoms without severe gastrointestinal side effects. Additionally, it inhibited the expression of pro-inflammatory molecules such as iNOS and COX-2, contributing to the reduction of arthritis symptoms. Notably, CA treatment prevented the common side effects of traditional RA treatments like corticosteroids and non-steroidal anti-inflammatory drugs (NSAIDs), including weight loss, bone degradation, and gastric ulcers. CONCLUSIONS: These findings suggest that CA, through specific enzyme inhibition, offers a compelling alternative therapeutic approach for RA. Further research is warranted to explore the potential of CA in other arthritis models and its suitability for human RA treatment.

CA significantly reduces inflammation in FCA induced arthritis model.CA treatment inhibits key pro-inflammatory molecules, including mPGES-1 and COX-2In silico docking studies confirm the affinity of CA to mPGES-1.CA prevents bone loss and avoids side effects seen with standard treatments.Antioxidant properties of CA counteract oxidative stress related to chronic inflammation.

Inhibition of Monoamine Oxidases by Pyridazinobenzylpiperidine Derivatives.

Monoamine oxidase inhibitors (MAOIs) have been crucial in the search for anti-neurodegenerative medications and continued to be a vital source of molecular and mechanistic diversity. Therefore, the search for selective MAOIs is one of the main areas of current drug development. To increase the effectiveness and safety of treating Parkinson's disease, new scaffolds for reversible MAO-B inhibitors are being developed. A total of 24 pyridazinobenzylpiperidine derivatives were synthesized and evaluated for MAO. Most of the compounds showed a higher inhibition of MAO-B than of MAO-A. Compound S5 most potently inhibited MAO-B with an IC50 value of 0.203 µM, followed by S16 (IC50 = 0.979 µM). In contrast, all compounds showed weak MAO-A inhibition. Among them, S15 most potently inhibited MAO-A with an IC50 value of 3.691 µM, followed by S5 (IC50 = 3.857 µM). Compound S5 had the highest selectivity index (SI) value of 19.04 for MAO-B compared with MAO-A. Compound S5 (3-Cl) showed greater MAO-B inhibition than the other derivatives with substituents of -Cl > -OCH3 > -F > -CN > -CH3 > -Br at the 3-position. However, the 2- and 4-position showed low MAO-B inhibition, except S16 (2-CN). In addition, compounds containing two or more substituents exhibited low MAO-B inhibition. In the kinetic study, the Ki values of S5 and S16 for MAO-B were 0.155 ± 0.050 and 0.721 ± 0.074 µM, respectively, with competitive reversible-type inhibition. Additionally, in the PAMPA, both lead compounds demonstrated blood-brain barrier penetration. Furthermore, stability was demonstrated by the 2V5Z-S5 complex by pi-pi stacking with Tyr398 and Tyr326. These results suggest that S5 and S16 are potent, reversible, selective MAO-B inhibitors that can be used as potential agents for the treatment of neurological disorders.

Design and Synthesis of the Linezolid Bioisosteres to Resolve the Serotonergic Toxicity Associated with Linezolid.

Serotonergic toxicity due to MAO enzyme inhibition is a significant concern when using linezolid to treat MDR-TB. To address this issue, we designed linezolid bioisosteres with a modified acetamidomethyl side chain at the C-5 position of the oxazolidine ring to balance activity and reduce toxicity. Among these bioisosteres, R7 emerged as a promising candidate, demonstrating greater effectiveness against M. tuberculosis (Mtb) H37Rv cells with an MIC of 2.01 µM compared to linezolid (MIC = 2.31 µM). Bioisostere R7 also exhibited remarkable activity (MIC50) against drug-resistant Mtb clinical isolates, with values of 0.14 µM (INHR, inhA+), 0.53 µM (INHR, katG+), 0.24 µM (RIFR, rpoB+), and 0.92 µM (INHR INHR, MDR). Importantly, it was >6.52 times less toxic as compared to the linezolid toward the MAO-A and >64 times toward the MAO-B enzyme, signifying a substantial improvement in its drug safety profile.

MzDOCK: A free ready-to-use GUI-based pipeline for molecular docking simulations.

Molecular docking is by far the most preferred approach in structure-based drug design for its effectiveness to predict the scoring and posing of a given bioactive small molecule into the binding site of its pharmacological target. Herein, we present MzDOCK, a new GUI-based pipeline for Windows operating system, designed with the intent of making molecular docking easier to use and higher reproducible even for inexperienced people. By harmonic integration of python and batch scripts, which employs various open source packages such as Smina (docking engine), OpenBabel (file conversion) and PLIP (analysis), MzDOCK includes many practical options such as: binding site configuration based on co-crystallized ligands; generation of enantiomers from SMILES input; application of different force fields (MMFF94, MMFF94s, UFF, GAFF, Ghemical) for energy minimization; retention of selectable ions and cofactors; sidechain flexibility of selectable binding site residues; multiple input file format (SMILES, PDB, SDF, Mol2, Mol); generation of reports and of pictures for interactive visualization. Users can download for free MzDOCK at the following link: https://github.com/Muzatheking12/MzDOCK.

Enzyme Inhibition Assays for Monoamine Oxidase.

Monoamine oxidase (MAO) catalyzes the oxidative deamination of monoamines with two isoforms, namely, MAO-A and MAO-B, in mitochondrial outer membranes. These two types of MAO-A and MAO-B participate in changes in levels of neurotransmitter such as serotonin (5-hydroxytryptamine) and dopamine. Selective MAO-A inhibitors have been targeted for anti-depression treatment, while selective MAO-B inhibitors are targets of therapeutic agents for Alzheimer's disease and Parkinson's disease. For this reason, study on the development of MAO inhibitors has recently become important. Here, we describe methods of MAO activity assay, especially continuous spectrophotometric methods, which give relatively high accuracy. MAO-A and MAO-B can be assayed using kynuramine and benzylamine as substrates, respectively, at 316 nm and 250 nm, respectively, to measure their respective products, 4-hydroxyquinoline and benzaldehyde. Inhibition degree and pattern can be analyzed by using the Lineweaver-Burk and secondary plots in the presence of inhibitor, and reversibility of inhibitor can be determined by using the dialysis method.

Machine learning driven web-based app platform for the discovery of monoamine oxidase B inhibitors.

Monoamine oxidases (MAOs), specifically MAO-A and MAO-B, play important roles in the breakdown of monoamine neurotransmitters. Therefore, MAO inhibitors are crucial for treating various neurodegenerative disorders, including Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, we developed a novel cheminformatics pipeline by generating three diverse molecular feature-based machine learning-assisted quantitative structural activity relationship (ML-QSAR) models concerning MAO-B inhibition. PubChem fingerprints, substructure fingerprints, and one-dimensional (1D) and two-dimensional (2D) molecular descriptors were implemented to unravel the structural insights responsible for decoding the origin of MAO-B inhibition in 249 non-reductant molecules. Based on a random forest ML algorithm, the final PubChem fingerprint, substructure fingerprint, and 1D and 2D molecular descriptor prediction models demonstrated significant robustness, with correlation coefficients of 0.9863, 0.9796, and 0.9852, respectively. The significant features of each predictive model responsible for MAO-B inhibition were extracted using a comprehensive variance importance plot (VIP) and correlation matrix analysis. The final predictive models were further developed as a web application, MAO-B-pred ( https://mao-b-pred.streamlit.app/ ), to allow users to predict the bioactivity of molecules against MAO-B. Molecular docking and dynamics studies were conducted to gain insight into the atomic-level molecular interactions between the ligand-receptor complexes. These findings were compared with the structural features obtained from the ML-QSAR models, which supported the mechanistic understanding of the binding phenomena. The presented models have the potential to serve as tools for identifying crucial molecular characteristics for the rational design of MAO-B target inhibitors, which may be used to develop effective drugs for neurodegenerative disorders.

Isatin-tethered halogen-containing acylhydrazone derivatives as monoamine oxidase inhibitor with neuroprotective effect.

Sixteen isatin-based hydrazone derivatives (IS1-IS16) were synthesized and assessed for their ability to inhibit monoamine oxidases (MAOs). All the molecules showed improved inhibitory MAO-B activity compared to MAO-A. Compound IS7 most potently inhibited MAO-B with an IC50 value of 0.082 µM, followed by IS13 and IS6 (IC50 = 0.104 and 0.124 µM, respectively). Compound IS15 most potently inhibited MAO-A with an IC50 value of 1.852 µM, followed by IS3 (IC50 = 2.385 µM). Compound IS6 had the highest selectivity index (SI) value of 263.80, followed by IS7 and IS13 (233.85 and 212.57, respectively). In the kinetic study, the Ki values of IS6, IS7, and IS13 for MAO-B were 0.068 ± 0.022, 0.044 ± 0.002, and 0.061 ± 0.001 µM, respectively, and that of IS15 for MAO-A was 1.004 ± 0.171 µM, and the compounds were reversible-type inhibitors. The lead compounds were central nervous system (CNS) permeable, as per parallel artificial membrane permeability assay (PAMPA) test results. The lead compounds were examined for their cytotoxicity and potential neuroprotective benefits in hazardous lipopolysaccharide (LPS)-exposed SH-SY5Y neuroblastoma cells. Pre-treatment with lead compounds enhanced anti-oxidant levels (SOD, CAT, GSH, and GPx) and decreased ROS and pro-inflammatory cytokine (IL-6, TNF-alpha, and NF-kB) production in LPS-intoxicated SH-SY5Y cells. To confirm the promising effects of the compound, molecular docking, dynamics, and MM-GBSA binding energy were used to examine the molecular basis of the IS7-MAO-B interaction. Our findings indicate that lead compounds are potential therapeutic agents to treat neurological illnesses, such as Parkinson's disease.

Correction: Isatin-based benzyloxybenzene derivatives as monoamine oxidase inhibitors with neuroprotective effect targeting neurodegenerative disease treatment.

[This corrects the article DOI: 10.1039/D3RA07035B.].

Inhibiting Monoamine Oxidase in CNS and CVS would be a Promising Approach to Mitigating Cardiovascular Complications in Neurodegenerative Disorders.

The flavoenzyme monoamine oxidases (MAOs) are present in the mitochondrial outer membrane and are responsible for the metabolism of biogenic amines. MAO deamination of biological amines produces toxic byproducts such as amines, aldehydes, and hydrogen peroxide, which are significant in the pathophysiology of multiple neurodegenerative illnesses. In the cardiovascular system (CVS), these by-products target the mitochondria of cardiac cells leading to their dysfunction and producing redox imbalance in the endothelium of the blood vessels. This brings up the biological relationship between the susceptibility of getting cardiovascular disorders in neural patients. In the current scenario, MAO inhibitors are highly recommended by physicians worldwide for the therapy and management of various neurodegenerative disorders. Many interventional studies reveal the benefit of MAO inhibitors in CVS. Drug candidates who can target both the central and peripheral MAO could be a better to compensate for the cardiovascular comorbidities observed in neurodegenerative patients.

Discerning of isatin-based monoamine oxidase (MAO) inhibitors for neurodegenerative disorders by exploiting 2D, 3D-QSAR modelling and molecular dynamics simulation.

Almost a billion people worldwide suffer from neurological disorders, which pose public health challenges. An important enzyme that is well-known for many neurodegenerative illnesses is monoamine oxidase (MAO). Although several promising drugs for the treatment of MAO inhibition have recently been examined, it is still necessary to identify the precise structural requirements for robust efficacy. Atom-based, field-based, and GA-MLR (genetic algorithm multiple linear regression) models were created for this investigation. All of the models have strong statistical (R2 and Q2) foundations because of both internal and external validation. Our dataset's molecule has a higher docking score than safinamide, a well-known and co-crystallized MAO-B inhibitor, as we also noticed. Using the SwissSimilarity platform, we further inquired which of our docked molecules would be the best for screening. We chose ZINC000016952895 as the screen molecule with the best binding docking score (XP score = -13.3613). Finally, the 100 ns for the ZINC000016952895-MAO-B complex in our MD investigations is stable. For compounds that we hit, also anticipate ADME properties. Our research revealed that the successful compound ZINC000016952895 might pave the way for the future development of MAO inhibitors for the treatment of neurological disease.Communicated by Ramaswamy H. Sarma.

In silico development of potential InhA inhibitors through 3D-QSAR analysis, virtual screening and molecular dynamics.

Tuberculosis is one of the most ancient infectious diseases known to mankind predating upper Paleolithic era. In the current scenario, treatment of drug resistance tuberculosis is the major challenge as the treatment options are limited, less efficient and more toxic. In our study we have developed an atom based 3D QSAR model, statistically validated sound with R2 > 0.90 and Q2 > 0.72 using reported direct inhibitors of InhA (2018-2022), validated by enzyme inhibition assay. The model was used to screen a library of 3958 molecules taken from Binding DB and candidates molecules with promising predicted activity value (pIC50) > 5) were selected for further analyzed screening by using molecular docking, ADME profiling and molecular dynamic simulations. The lead molecule, ZINC11536150 exhibited good docking score (glideXP = -11.634 kcal/mol) compared to standard triclosan (glideXP = -7.129 kcal/mol kcal/mol) and through molecular dynamics study it was observed that the 2nv6-complex of ZINC11536150 with Mycobacterium tuberculosis InhA (PDB entry: 2NV6) complex remained stable throughout the entire simulation time of 100 ns.Communicated by Ramaswamy H. Sarma.

"Click Chemistry": An Emerging Tool for Developing a New Class of Structural Motifs against Various Neurodegenerative Disorders.

Click chemistry is a set of easy, atom-economical reactions that are often utilized to combine two desired chemical entities. Click chemistry accelerates lead identification and optimization, reduces the complexity of chemical synthesis, and delivers extremely high yields without undesirable byproducts. The most well-known click chemistry reaction is the 1,3-dipolar cycloaddition of azides and alkynes to form 1,2,3-triazoles. The resulting 1,2,3-triazoles can serve as both bioisosteres and linkers, leading to an increase in their use in the field of drug discovery. The current Review focuses on the use of click chemistry to identify new molecules for treating neurodegenerative diseases and in other areas such as peptide targeting and the quantification of biomolecules.